ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

The importance of an exaggerated attention bottleneck for understanding psychopathy

The psychopath has long captured the imagination. A name such as Ted Bundy evokes a morbid curiosity. The crimes committed by Bundy are so cruel that it is hard to imagine how someone could do such things. In this review we discuss evidence that exaggeration in an attention bottleneck is one mechanism that makes it possible for psychopathic individuals to be adept at focusing on a single stimulus feature or goal but struggle to process multiple streams of information simultaneously. This exaggeration may partly explain the behavioral, affective, and social deficits that are apparent among psychopathic individuals. Further research on this attentional mechanism may promote a science that adequately captures the complexity of psychopathic behavior and offers new avenues for intervention

Differentiating patterns of substance misuse by subtypes of antisocial traits in male offenders

Among criminal offenders, two subtypes of antisocial traits, psychopathy and externalizing-only, are associated with an especially elevated risk for substance use disorders (SUDs). The present study examined the associations of these traits with patterns of substance misuse. In a sample of 1410 male offenders, we used diagnoses for alcohol, cannabis, opioids, and stimulants to examine the association between antisocial traits and SUD severity, as well as, age at substance use initiation. Results indicated that externalizing-only, but not psychopathic, traits predicted greater severity of SUDs (i.e. increased likelihood of dependence) across all substances. By contrast, psychopathic, but not externalizing-only, traits predicted earlier initiation of use across all substances. These differential patterns of substance misuse may be a reflection of distinct psychobiological processes. Ultimately, parsing the patterns of substance use across a continuum of clinically heterogeneous samples, rather than within circumscribed diagnostic categories, might help to refine the phenotype and improve the prediction of substance-related problems

Classification and treatment of antisocial individuals: From behavior to biocognition

Item does not contain fulltextAntisocial behavior is a heterogeneous construct that can be divided into subtypes, such as antisocial personality and psychopathy. The adverse consequences of antisocial behavior produce great burden for the perpetrators, victims, family members, and for society at-large. The pervasiveness of antisocial behavior highlights the importance of precisely characterizing subtypes of antisocial individuals and identifying specific factors that are etiologically related to such behaviors to inform the development of targeted treatments. The goals of the current review are (1) to briefly summarize research on the operationalization and assessment of antisocial personality and psychopathy; (2) to provide an overview of several existing treatments with the potential to influence antisocial personality and psychopathy; and (3) to present a procedure for integrating and using biological and cognitive measures as starting points to more precisely characterize and treat these individuals. A focus on integrating factors at multiple levels of analysis will uncover person-specific characteristics and highlight potential targets for treatment to alleviate the burden caused by antisocial behavior.19 p

A comparison of latent profiles in antisocial male offenders

Item does not contain fulltextPurpose: Within forensic settings, the tools used to evaluate subtypes of antisocial offenders (e.g. interview-based measures such as the Psychopathy Checklist) are expensive and time consuming. The purpose of the present study was to identify and validate distinct antisocial profiles in male offenders using questionnaires. In the future, this approach could help us identify antisocial profiles in a cost-effective way. Method: First, we investigated the robustness and replicability of the profiles reported by previous profiling studies by performing latent profile analysis using the Self-Report Psychopathy Short-Form. Second, we studied how these profiles were linked to personality correlates that have been used to differentiate between groups of antisocial offenders. Third, we investigated how each profile was related to a broad range of behaviours seen in antisocial populations. Result: Four antisocial profiles were identified: generic offenders, impulsive-antisocial traits offenders, non-antisocial psychopathic traits offenders, and psychopathic traits offenders. The validity of these profiles was supported by their links with external personality and behavioural correlates. Conclusion: Consistent with previous research using interview-based measures, these findings provide support for the presence of four distinct antisocial profiles based on self-report psychopathy scores in male offenders. Furthermore, findings provide relatively extensive and multifaceted characterizations of each profile.9 p

Classifying conduct disorder using a biopsychosocial model and machine learning method

Background: Conduct disorder (CD) is a common syndrome with far-reaching effects. Risk factors for the development of CD span social, psychological, and biological domains. Researchers note that predictive models of CD are limited if the focus is on a single risk factor or even a single domain. Machine learning methods are optimized for the extraction of trends across multidomain data but have yet to be implemented in predicting the development of CD. Methods: Social (e.g., family, income), psychological (e.g., psychiatric, neuropsychological), and biological (e.g., resting-state graph metrics) risk factors were measured using data from the baseline visit of the Adolescent Brain Cognitive Development Study when youth were 9 to 10 years old (N = 2368). Applying a feed-forward neural network machine learning method, risk factors were used to predict CD diagnoses 2 years later. Results: A model with factors that included social, psychological, and biological domains outperformed models representing factors within any single domain, predicting the presence of a CD diagnosis with 91.18% accuracy. Within each domain, certain factors stood out in terms of their relationship to CD (social: lower parental monitoring, more aggression in the household, lower income; psychological: greater attention-deficit/hyperactivity disorder and oppositional defiant disorder symptoms, worse crystallized cognition and card sorting performance; biological: disruptions in the topology of subcortical and frontoparietal networks). Conclusions: The development of an accurate, sensitive, and specific predictive model of CD has the potential to aid in prevention and intervention efforts. Key risk factors for CD appear best characterized as reflecting unpredictable, impulsive, deprived, and emotional external and internal contexts

Psychopathy

Psychopathy is a personality disorder characterized by a constellation of affective, interpersonal, lifestyle and antisocial features whose antecedents can be identified in a subgroup of young people showing severe antisocial behaviour. The prevalence of psychopathy in the general population is thought to be ~1%, but is up to 25% in prisoners. The aetiology of psychopathy is complex, with contributions of both genetic and environmental risk factors, and gene-environment interactions and correlations. Psychopathy is characterized by structural and functional brain abnormalities in cortical (such as the prefrontal and insular cortices) and subcortical (for example, the amygdala and striatum) regions leading to neurocognitive disruption in emotional responsiveness, reinforcement-based decision-making and attention. Although no effective treatment exists for adults with psychopathy, preliminary intervention studies targeting key neurocognitive disturbances have shown promising results. Given that psychopathy is often comorbid with other psychiatric disorders and increases the risk of physical health problems, educational and employment failure, accidents and criminality, the identification of children and young people at risk for this personality disorder and preventative work are important. Indeed, interventions that target the antecedents of psychopathic features in children and adolescents have been found to be effective

Author Correction: Psychopathy (Nature Reviews Disease Primers, (2021), 7, 1, (49), 10.1038/s41572-021-00282-1)

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